Triple
T32663554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Амгунь |
E835092
|
entity |
| Predicate | близлежащийКрупныйГород |
P112043
|
FINISHED |
| Object | Комсомольск-на-Амуре |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Комсомольск-на-Амуре | Statement: [Амгунь, близлежащийКрупныйГород, Комсомольск-на-Амуре]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: близлежащийКрупныйГород Context triple: [Амгунь, близлежащийКрупныйГород, Комсомольск-на-Амуре]
-
A.
largestNearbyCity
Indicates that one city is the largest (by population, area, or another defined metric) among the cities located within a specified nearby region of another place or city.
-
B.
adjacentMajorCity
Indicates that one major city is geographically next to or directly bordering another major city.
-
C.
hasNearbyCityFunction
Indicates that one entity serves as a nearby urban center or city-like service hub for another entity.
-
D.
hasNearbyMajorCityCountry
Indicates that an entity has a nearby major city located in the specified country.
-
E.
nearestLargeUrbanArea
chosen
Indicates that one entity is the closest major city or large urban center to the other entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f349303ccc8190a70d0f6e8a21d3fb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c7a66d3881908f5aec4ccd11d60d |
completed | May 3, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:08 a.m.